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teaching:projh402 [2020/10/01 12:35] mahmsakr [Geospatial Trajectory Data Cleaning] |
teaching:projh402 [2020/10/01 16:51] ezimanyi [Visualization of Moving Objects on the Web] |
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| - | ===== Visualization Moving Objects on the Web ===== | + | ===== Visualization of Moving Objects on the Web ===== |
| - | <TBD> | + | There are several open source platforms for publishing spatial data and interactive mapping applications to the web. Two populars ones are [[https://mapserver.org/|MapServer]] and [[http://geoserver.org/|GeoServer]], which are written, respectively, in C and in Java. |
| + | Newer platforms exists, such as [[https://kepler.gl/|kepler.gl]], which were designed for handling large-scale data sets. | ||
| + | However, these platforms are used for static spatial data and are unable to cope with moving objects. The goal of the project is to extend one of these platforms with spatio-temporal data types in order to be able to display animated maps. | ||
| ===== Implementing TSBS on MobilityDB ===== | ===== Implementing TSBS on MobilityDB ===== | ||
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| ===== Geospatial Trajectory Similarity Measure ===== | ===== Geospatial Trajectory Similarity Measure ===== | ||
| + | One of the main functions for a wide range of application domains is to measure the similarity between two moving objects' trajectories. This is desirable for similarity-based retrieval, classification, clustering and other querying and mining tasks over moving objects' data. The existing movement similarity measures can be classified into two classes: (1) spatial similarity that focuses on finding trajectories with similar geometric shapes, ignoring the temporal dimension; and (2) spatio-temporal similarity that takes into account both the spatial and the temporal dimensions of movement data. | ||
| + | The goal of this project is to survey and to prototype in MobilityDB the state of art methods in trajectory similarity. Since it is a complex problem, these outcomes should serve as a base for a thesis project to propose effective and efficient trajectory similarity measures. | ||
| ===== Spatiotemporal k-Nearest Neighbour (kNN) Queries ===== | ===== Spatiotemporal k-Nearest Neighbour (kNN) Queries ===== | ||
| + | An example of continuous kNN is when the GPS device of the vehicle initiates a query | ||
| + | to find the three closest gas stations to the vehicle at any time instant during its trip from source to destination. According to the location of the vehicle, the set of three nearest gas stations can change. The result is thus a set of intervals, where very interval is associated with a set of three gas stations. The challenge in this type of query is to find an efficient incremental way of evaluation. | ||
| + | The goal of the project is to survey the state of art in continuous kNN queries, and to prototype selected methods in MobilityDB. Since it is a complex problem, these outcomes should serve as a base for a more elaborate thesis project. | ||